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Found 2 papers, 2 papers with code
Debiasing Pre-Trained Language Models via Efficient Fine-Tuning
An explosion in the popularity of transformer-based language models (such as GPT-3, BERT, RoBERTa, and ALBERT) has opened the doors to new machine learning applications involving language modeling, text generation, and more.
LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks
LIFT does not make any changes to the model architecture or loss function, and it solely relies on the natural language interface, enabling "no-code machine learning with LMs."
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